Productivity of crops grown for human consumption is at risk due to the incidence of pests, especially weeds. pathogens and animal pests. Crop losses due to these harmful organisms can be substantial and may be prevented, or reduced, by crop protection measures. An overview is given on different types of crop losses as well as on various methods of pest control developed during the last century. Estimates on potential and actual losses despite the Current crop protection practices Lire given for wheat. rice. maize. potatoes, soybeans, And cotton for the period 2001-03 on a regional basis ( 19 regions) as well as for the global total. Among crops, the total global potential loss due to pests varied from about 50% in wheat to more than 80% ill cotton production. The responses Lire estimated as losses of 26-29% for soybean, wheat and cotton, and 31 37 and 40% for maize, rice and potatoes. respectively. Overall, weeds produced the highest potential loss (34%), with animal pests and pathogens being less important (losses of IS and 16%). The efficacy of crop protection was higher in cash crops than in food crops. Weed control call be managed mechanically or chemically, therefore worldwide efficacy was considerably higher than for the control of animal pests or diseases, which rely heavily on synthetic chemicals. Regional differences in efficacy are outlined. Despite a clear increase in pesticide use. crop losses have not significantly decreased during the last 40 years. However. pesticide use has enabled farmers to modify production systems and to increase crop productivity Without sustaining the higher losses likely to occur from an increased Susceptibility to the damaging, effect of pests. The concept of integrated pest/crop management includes a threshold concept for the application of pest control measures and reduction in the amount/frequency of pesticides applied to an economically and ecologically acceptable level. Often minor crop losses are economically acceptable; however. all increase ill crop productivity without adequate crop protection does not make sense, because an increase in attainable yields is often associated with an increased vulnerability to damage inflicted by pests.
This review compares and contrasts postharvest food losses (PHLs) and waste in developed countries (especially the USA and the UK) with those in less developed countries (LDCs), especially the case of cereals in sub-Saharan Africa. Reducing food losses oilers an important way of increasing food availability without requiring additional production resources, and in LDCs it can contribute to rural development and poverty reduction by improving agribusiness livelihoods. The critical factors governing PHLs and food waste are mostly after the farm gate in developed countries but before the farm gate in LDCs. In the foreseeable future (e.g. up to 2030), the main drivers for reducing PHLs differ: in the developed world, they include consumer education campaigns, carefully targeted taxation and private and public sector partnerships sharing the responsibility for loss reduction. The LDCs' drivers include more widespread education of farmers in the causes of PHLs; better infrastructure to connect smallholders to markets; more effective value chains that provide sufficient financial incentives at the producer level; opportunities to adopt collective marketing and better technologies supported by access to microcredit; and the public and private sectors sharing the investment costs and risks in market-orientated interventions.
The present study employed the Heckman sample selection model to analyse the two- step process of adaptation to climate change, which initially requires farmers' perception that climate is changing prior to responding to changes through adaptation. Farmers' perception of climate change was significantly related to the age of the head of the household, wealth, knowledge of climate change, social capital and agro-ecological settings. Factors significantly affecting adaptation to climate change were: education of the head of the household, household size, whether the head of the household was male, whether livestock were owned, the use of extension services on crop and livestock production, the availability of credit and the environmental temperature.
The predicted 2-4 degrees C increment in temperature by the end of the 21st Century poses a threat to rice production. The impact of high temperatures at night is more devastating than day-time or mean daily temperatures. Booting and flowering are the stages most sensitive to high temperature, which may sometimes lead to complete sterility. Humidity also plays a vital role in increasing the spikelet sterility at increased temperature. Significant variation exists among rice germplasms in response to temperature stress. Flowering at cooler times of day, more pollen viability, larger anthers, longer basal dehiscence and presence of long basal pores are some of the phenotypic markers for high-temperature tolerance. Protection of structural proteins, enzymes and membranes and expression of heat shock proteins (HSPs) are some of the biochemical processes that can impart thermo-tolerance. All these traits should be actively exploited in future breeding programmes for developing heat-resistant cultivars. Replacement of heat-sensitive cultivars with heat-tolerant ones, adjustment of sowing time, choice of varieties with a growth duration allowing avoidance of peak stress periods, and exogenous application of plant hormones are some of the adaptive measures that will help in the mitigation of forecast yield reduction due to global warming.
There is a very significant, cost effective greenhouse gas (GHG) mitigation potential in agriculture. The annual mitigation potential in agriculture is estimated to be 4200, 2600 and 1600 Mt CO2 equiv/yr at C prices of 100, 50 and 20 US$/t CO2 equiv, respectively. The value of GHG mitigated each year is equivalent to 420 000, 130 000 and 32 000 million US$/yr for C prices of 100, 50 and 20 US$/t CO2 equiv, respectively. From both the mitigation and economic perspectives, we cannot afford to miss out on this mitigation potential. The challenge of agriculture within the climate change context is two-fold, both to reduce emissions and to adapt to a changing and more variable climate. The primary aim of the mitigation options is to reduce emissions of methane or nitrous oxide or to increase soil carbon storage. All the mitigation options, therefore, affect the carbon and/or nitrogen cycle of the agroecosystem in some way. This often not only affects the GHG emissions but also the soil properties and nutrient cycling. Adaptation to increased variability of temperature and rainfall involves increasing the resilience of the production systems. This may be done by improving soil water holding capacities through adding crop residues and manure to arable soils or by adding diversity to the crop rotations. Though some mitigation measures may have negative impacts on the adaptive capacity of farming systems, most categories of adaptation options for climate change have positive impacts on mitigation. These include: (1) measures that reduce soil erosion, (2) measures that reduce leaching of nitrogen and phosphorus, (3) measures for conserving soil moisture, (4) increasing the diversity of crop rotations by choices of species or varieties, (5) modification of microclimate to reduce temperature extremes and provide shelter, (6) land use change involving abandonment or extensification of existing agricultural land, or avoidance of the cultivation of new land. These adaptation measures will in general, if properly applied, reduce GHG emissions, by improving nitrogen use efficiencies and improving soil carbon storage. There appears to be a large potential for synergies between mitigation and adaptation within agriculture. This needs to be incorporated into economic analyses of the mitigation costs. The inter-linkages between mitigation and adaptation are, however, not very well explored and further studies are warranted to better quantify short-and long-term effects on suitability for mitigation and adaptation to climate change. In order to realize the full potential for agriculture in a climate change context, new agricultural production systems need to be developed that integrate bioenergy and food and feed production systems. This may possibly be obtained with perennial crops having low-environmental impacts, and deliver feedstocks for biorefineries for the production of biofuels, biomaterials and feed for livestock.
Nitrogen (N) is an essential element for plants and animals. Due to large inputs of mineral fertilizer, crop yields and livestock production in Europe have increased markedly over the last century, but as a consequence losses of reactive Nto air, soil and water have intensified as well. Two different models (CAPRI and MITERRA) were used to quantify the N flows in agriculture in the European Union (EU27), at country-level and for EU27 agriculture as a whole, differentiated into 12 main food categories. The results showed that the N footprint, defined as the totalNlosses to the environment per unit of product, varies widely between different food categories, with substantially higher values for livestock products and the highest values for beef (c. 500 gN/kg beef), as compared to vegetable products. The lowest N footprint of c. 2 gN/kg product was calculated for sugar beet, fruits and vegetables, and potatoes. The losses of reactive N were dominated by N leaching and run-off, and ammonia volatilization, with 0.83 and 0.88 due to consumption of livestock products. The N investment factors, defined as the quantity of new reactive N required to produce one unit of N in the product varied between 1.2 kg N/kg N in product for pulses to 15-20 kg N for beef.
Climate change is now unequivocal, particularly in terms of increasing temperature, increasing CO2 concentration, widespread melting of snow and ice and rising global average sea level, while the increase in the frequency of drought is very probable but not as certain. However, climate changes are not new and some of them have had dramatic impacts, such as the appearance of leaves about 400 million years ago as a response to a drastic decrease in CO2 concentration, the birth of agriculture due to the end of the last ice age about 11000 years ago and the collapse of civilizations due to the late Holocene droughts between 5000 and 1000 years ago. The climate changes that are occurring at present will have - and are already having - an adverse effect on food production and food quality with the poorest farmers and the poorest countries most at risk. The adverse effect is a consequence of the expected or probable increased frequency of some abiotic stresses such as heat and drought, and of the increased frequency of biotic stresses ( pests and diseases). In addition, climate change is also expected to cause losses of biodiversity, mainly in more marginal environments. Plant breeding has addressed both abiotic and biotic stresses. Strategies of adaptation to climate changes may include a more accurate matching of phenology to moisture availability using photoperiod-temperature response, increased access to a suite of varieties with different duration to escape or avoid predictable occurrences of stress at critical periods in crop life cycles, improved water use efficiency and a re-emphasis on population breeding in the form of evolutionary participatory plant breeding to provide a buffer against increasing unpredictability. ICARDA, in collaboration with scientists in Iran, Algeria, Jordan, Eritrea and Morocco, has recently started evolutionary participatory programmes for barley and durum wheat. These measures will go hand in hand with breeding for resistance to biotic stresses and with an efficient system of variety delivery to farmers.
Conservation agriculture (CA), defined as minimal soil disturbance (no-till) and permanent soil cover (mulch) combined with rotations, is a more sustainable cultivation system for the future than those presently practised. The present paper first introduces the reasons for tillage in agriculture and discusses how this age-old agricultural practice is responsible for the degradation of natural resources and soils. The paper goes on to introduce conservation tillage (CT), a minimum tillage and surface mulch practice that was developed in response to the severe wind erosion caused by mouldboard tillage of grasslands and referred to as the American dust bowl of the 1930s. CT is then compared with CA, a suggested improvement on CT, where no-till, mulch, and rotations significantly improve soil properties (physical, biological, and chemical) and other biotic factors, enabling more efficient use of natural resources. CA can improve agriculture through improvement in water infiltration and reducing erosion, improving soil surface aggregates, reducing compaction through promotion of biological tillage, increasing surface soil organic matter and carbon content, moderating soil temperatures, and suppressing weeds. CA also helps reduce costs of production, saves time, increases yield through more timely planting, reduces diseases and pests through stimulation of biological diversity, and reduces greenhouse gas emissions. Availability of suitable equipment is a major constraint to successful CA, but advances in design and manufacture of seed drills by local manufacturers are enabling farmers to experiment and accept this technology in many parts of the world. Estimates of farmer adoption of CA are close to 100 million ha in 2005, indicating that farmers are convinced of the benefits of this technology. The paper concludes that agriculture in the next decade will have to produce more food, sustainably, from less land through more efficient use of natural resources and with minimal impact on the environment in order to meet growing population demands. This will be a significant challenge for agricultural scientists, extension personnel, and farmers. Promoting and adopting CA management systems can help meet this complex goal.
Assessing carbon footprint (CF) of crop production in a whole crop life-cycle could provide insights into the contribution of crop production to climate change and help to identify possible greenhouse gas (GHG) mitigation options. In the current study, data for the major crops of China were collected from the national statistical archive on cultivation area, yield, application rates of fertilizer, pesticide, diesel, plastic film, irrigated water, etc. The CF of direct and indirect carbon emissions associated with or caused by these agricultural inputs was quantified with published emission factors. In general, paddy rice, wheat, maize and soybean of China had mean CFs of 2472, 794, 781 and 222 kg carbon equivalent (CE)/ha, and 0.37, 0.14, 0.12 and 0.10 kg CE/kg product, respectively. For dry crops (i.e. those grown without flooding the fields: wheat, maize and soybean), 0.78 of the total CFs was contributed by nitrogen (N) fertilizer use, including both direct soil nitrous oxide (N2O) emission and indirect emissions from N fertilizer manufacture. Meanwhile, direct methane (CH4) emissions contributed 0.69 on average to the total CFs of flooded paddy rice. Moreover, the difference in N fertilizer application rates explained 0.86-0.93 of the provincial variations of dry crop CFs while that in CH4 emissions could explain 0.85 of the provincial variation of paddy rice CFs. When a 30% reduction in N fertilization was considered, a potential reduction in GHGs of 60 megatonne (Mt) carbon dioxide equivalent from production of these crops was projected. The current work highlights opportunities to gain GHG emission reduction in production of crops associated with good management practices in China.
Brazil is one of the most important soybean producers in the world. Soybean is a very important crop for the country as it is used for several purposes, from food to biodiesel production. The levels of soybean yield in the different growing regions of the country vary substantially, which results in yield gaps of considerable magnitude. The present study aimed to investigate the soybean yield gaps in Brazil, their magnitude and causes, as well as possible solutions for a more sustainable production. The concepts of yield gaps were reviewed and their values for the soybean crop determined in 15 locations across Brazil. Yield gaps were determined using potential and attainable yields, estimated by a crop simulation model for the main maturity groups of each region, as well as the average actual famers' yield, obtained from national surveys provided by the Brazilian Government for a period of 32 years (1980-2011). The results showed that the main part of the yield gap was caused by water deficit, followed by sub-optimal crop management. The highest yield gaps caused by water deficit were observed mainly in the south of Brazil, with gaps higher than 1600 kg/ha, whereas the lowest were observed in Tapurah, Jatai, Santana do Araguaia and Uberaba, between 500 and 1050 kg/ha. The yield gaps caused by crop management were mainly concentrated in South-central Brazil. In the soybean locations in the mid-west, north and northeast regions, the yield gap caused by crop management was 2000 kg/ha. For reducing the present soybean yield gaps observed in Brazil, several solutions should be adopted by growers, which can be summarized as irrigation, crop rotation and precision agriculture. Improved dissemination of agricultural knowledge and the use of crop simulation models as a tool for improving crop management could further contribute to reduce the Brazilian soybean yield gap.
Phenological models are considered key tools for the short-term planning of viticultural activities and long-term impact assessment of climate change. In the present study, statistical phenological models were developed for budburst (BUD), flowering (FLO) and veraison (VER) of 16 grapevine varieties (autochthonous and international) from the Portuguese wine-making regions of Douro, Lisbon and Vinhos Verdes. For model calibration, monthly averages of daily minimum (Tmin), maximum (Tmax) and mean (Tmean) temperatures were selected as potential regressors by a stepwise methodology. Significant predictors included Tmin in January-February-March for BUD, Tmax in March-April for FLO, and Tmin, Tmax and Tmean in March-July for VER. Developed models showed a high degree of accuracy after validation, representing 071 of total variance for BUD, 083 for FLO and 078 for VER. Model errors were in most cases < 5 days, outperforming classic growing degree-day models, including models based on optimized temperature thresholds for each variety. Applied to the future scenarios RCP45/85, projections indicate earlier phenophase onset and shorter interphases for all varieties. These changes may bring significant challenges to the Portuguese wine-making sector, highlighting the need for suitable adaptation/mitigation strategies, to ensure its future sustainability.
A growing trend for nutraceutical and gluten-free cereal-based products highlights the need for development of new products. Buckwheat is one of the potential candidates for such products and the present paper reviews the functional and nutraceutical compounds present in common buckwheat (Fagopyrum esculentum) and tartary buckwheat (Fagopyrum tataricum). The vital functional substances in buckwheat are flavonoids, phytosterols, fagopyrins, fagopyritols, phenolic compounds, resistant starch, dietary fibre, lignans, vitamins, minerals and antioxidants, which make it a highly active biological pseudocereal. Cholesterol-lowering effects that lessen the problems of constipation and obesity are important health benefits that can be achieved through the functional substances of buckwheat.
Accurate field data on the paddock area affected by cow urine depositions are critical to the estimation and modelling of nitrogen (N) losses and N management in grazed pasture systems. A new technique using survey-grade global positioning system (GPS) technology was developed to precisely measure the paddock spatial area coverage, diversity and distribution of dairy cattle urine patches in grazed paddocks over time. A 4-year study was conducted on the Lincoln University Dairy Farm (LUDF), Canterbury, New Zealand, from 2003 to 2007. Twelve field plots, each 100m(2) in area, were established on typical grazing areas of the farm. All urine and dung deposits within the plots were visually identified, the pasture response area (radius) measured and position marked with survey-grade GPS. The plots were grazed as part of the normal grazing rotation of the farm and urine and dung deposits measured at 12-week intervals. The data were collated using spatial (GIS) software and an assessment of annual urine patch coverage and spatial distribution was made. Grazing intensities ranged from 17645 to 30295 cow grazing h/ha/yr. Mean annual areas of urine patches ranged from 0.34 to 0.40 m(2) (4-year mean 0.37 +/- 0.009m(2)), with small but significant variation between years and seasons. Mean annual urine patch numbers were 6240 +/- 124 patches/ha/yr. The mean proportional area coverage for a single sampling event or season was 0.058 and the mean proportional annual urine patch coverage was 0.232 +/- 0.0071. There was a strong linear relationship between annual cow grazing h/ha and urine patch numbers/ha (R-2=0.69) and also annual urine patch area coverage (R-2=0.77). Within the stocking densities observed in this study, an annual increase of 10 000 cow grazing h/ha increased urine patch numbers by 1800 urine patches/ha/yr and annual urine patch area coverage by 0.07. This study presents new quantitative data on urine patch size, numbers and the spatial coverage of patches on a temporal basis.
Sixteen Suffolk lambs with 29 +/- 2.0 kg body weight were housed in individual cages for 60 days and allotted to four treatments in a completely randomized design to determine the effect of administration of Salix babylonica (SB) extract and/or exogenous enzymes (ZADO (R)) on lamb performance. Lambs were fed with 300 g/kg concentrate (160 g crude protein (CP)/kg, 13.4 MJ metabolizable energy (ME)/kg dry matter (DM)) and 700 g/kg maize silage (80 g/kg CP, 11.7 MJ ME/kg DM) as a basal diet (control). Another three treatments were tested; the SB extract was administered at 30 ml/day (SB) and exogenous enzymes ZADO (R) (i.e. an exogenous enzyme cocktail in a powder form) directly fed at 10 g/day (EZ), while the last treatment contained ZADO (R) at 10 g/day + SB extract at 30 ml/day (EZSB). Lambs of the treatment EZSB had the greatest average daily weight gain (ADG) and feed conversion throughout the period of the experiment. However, during the first 30 days SB was more effective for ADG than EZ and vice versa during the last 30 days of the experiment. Water consumption was greater for SB, followed by EZ and EZSB compared to the control. Intakes of DMand organicmatter (OM) were the highest in EZSB followed by EZ, which had the greatest neutral detergent fibre, acid detergent fibre (ADF) and nitrogen (N) intakes. The EZSB treatment had the greatest DM and OM digestibilities compared to the other treatments; however, SB had the greatest ADF digestibility. Combination of EZ and SB had the best N balance. Allantoin, total purine derivatives (PD), allantoin : -creatinine ratio, and PD: creatinine ratio were increased in EZSB compared to the other treatments. However, EZ supplementation increased uric acid concentration, whereas the microbial N (g N/day) and metabolizable protein (g N/day) were increased in EZSB versus the other treatments. It can be concluded that addition of 10 g ZADO (R) in combination with S. babylonica extract at 30 ml/day in the diet of lambs increased feed intake, nutrient digestibility and daily gain, with a positive impact on the use of N and microbial protein synthesis.
EU milk quota deregulation has forced many farmers to reconsider the factors that will limit milk production into the future. Factors other than milk quota such as land, labour, capital, stock, etc. will become the limiting factor for many in a post-EU milk quota scenario. While it can be postulated what the limits to production will be in a post-quota scenario, how farmers react will determine the future direction of the industry. In order to determine the future attitudes and intentions and to identify the key factors influencing farmers who intend to expand, exit, remain static or contract their businesses in the future, a survey of a large group of Irish commercial dairy farmers was carried out. The telephone survey sample was chosen randomly, based on a proportional representation of suppliers to the largest milk processor in Ireland. The sample (780 suppliers) was broken down by quota size (five quota categories, Q1-Q5), supplier region and system of production. The sample was analysed to determine the effect of key survey variables on the future intentions of dairy farmers. The survey was completed by 659 suppliers (0.82 of the sample). The proportions of farmers intending to expand were 0.28, 0.47, 0.61, 0.61 and 0.56, respectively, for Q1-Q5, while the proportions intending to exit were 0.27, 0.18, 0.08, 0.09 and 0.08, respectively. Farmers who were intent on expanding had larger total farm areas, larger milk tank capacity per litre of milk quota, more modern milking facilities, more available cow housing and more housing that could be converted at a relatively low cost and were more likely to have a successor. Of those expanding, 0.60 wanted milk quotas abolished, while 0.36 of those planning to exit wanted milk quotas abolished. The level of expansion was affected by business scale, dairy stocking rate, the additional labour required with expansion and total and milking platform farm size.
The analysis of series of crop variety trials has a long history with the earliest approaches being based on ANOVA methods. Kempton (1984) discussed the inadequacies of this approach.. summarized the alternatives available at that time and noted that all of these approaches could be classified as multiplicative models. Recently, mixed model approaches have become popular for the analysis of series of variety trials. There are numerous reasons for their use, including the ease with which incomplete data (not all varieties in all trials) can be handled and the ability to appropriately model within-trial error variation. Currently, the most common mixed model approaches for series of variety trials are mixed model versions of the methods summarized by Kempton(1984). In the present paper a general formulation that encompasses all of these methods is described, then individual methods are considered in detail.
In the current Dutch protein evaluation system (the DVE/OEB1991 system), two characteristics are calculated for each feed: true protein digested in the intestine (DVE) and the rumen degradable protein balance (OEB). Of these, DVE represents the protein value of a feed, while OEB is the difference between the potential microbial protein synthesis (MPS) on the basis of available rumen degradable protein and that on the basis of available rumen degradable energy. DVE can be separated into three components: (i) feed crude protein undegraded in the rumen but digested in the small intestine, (ii) microbial true protein synthesized in the rumen and digested in the small intestine, and (iii) endogenous protein lost in the digestive processes. Based on new research findings, the DVE/OEB1991 system has recently been updated to the DVE/OEB2010 system. More detail and differentiation is included concerning the representation of chemical components in feed, the rumen degradation characteristics of these components, the efficiency of MPS and the fractional passage rates. For each chemical component, the soluble, washout, potentially degradable and truly non-degradable fractions are defined with separate fractional degradation rates. Similarly, fractional passage rates for each of these fractions were identified and partly expressed as a function of fractional degradation rate. Efficiency of MPS is related to the various fractions of the chemical components and their associated fractional passage rates. Only minor changes were made with respect to the amount of DVE required for maintenance and production purposes of the animal. Differences from other current protein evaluation systems, viz. the Cornell Net Carbohydrate and Protein system and the Feed into Milk system, are discussed.
The present paper presents a meta-analysis of the economic and agronomic performance of genetically modified (GM) crops worldwide. Bayesian, classical and non-parametric approaches were used to evaluate the performance of GM crops v. their conventional counterparts. The two main GM crop traits (herbicide tolerant (HT) and insect resistant (Bt)) and three of the main GM crops produced worldwide (Bt cotton, HT soybean and Bt maize) were analysed in terms of yield, production cost and gross margin. The scope of the analysis covers developing and developed countries, six world regions, and all countries combined. Results from the statistical analyses indicate that GM crops perform better than their conventional counterparts in agronomic and economic (gross margin) terms. Regarding countries' level of development, GM crops tend to perform better in developing countries than in developed countries, with Bt cotton being the most profitable crop grown.
Eleven widely used crop simulation models (APSIM, CERES, CROPSYST, COUP, DAISY, EPIC, FASSET, HERMES, MONICA, STICS and WOFOST) were tested using spring barley (Hordeum vulgare L.) data set under varying nitrogen (N) fertilizer rates from three experimental years in the boreal climate of Jokioinen, Finland. This is the largest standardized crop model inter-comparison under different levels of N supply to date. The models were calibrated using data from 2002 and 2008, of which 2008 included six N rates ranging from 0 to 150 kg N/ha. Calibration data consisted of weather, soil, phenology, leaf area index (LAI) and yield observations. The models were then tested against new data for 2009 and their performance was assessed and compared with both the two calibration years and the test year. For the calibration period, root mean square error between measurements and simulated grain dry matter yields ranged from 170 to 870 kg/ha. During the test year 2009, most models failed to accurately reproduce the observed low yield without N fertilizer as well as the steep yield response to N applications. The multi-model predictions were closer to observations than most single-model predictions, but multi-model mean could not correct systematic errors in model simulations. Variation in soil N mineralization and LAI development due to differences in weather not captured by the models most likely was the main reason for their unsatisfactory performance. This suggests the need for model improvement in soil N mineralization as a function of soil temperature and moisture. Furthermore, specific weather event impacts such as low temperatures after emergence in 2009, tending to enhance tillering, and a high precipitation event just before harvest in 2008, causing possible yield penalties, were not captured by any of the models compared in the current study.